Distribution Of Diversity Research Articles

Seasonality of primary production explains the richness of pioneering benthic communities

A pattern of increasing species richness from the poles to the equator is frequently observed in many animal taxa. Ecological limits, determined by the abiotic conditions and biotic interactions within an environment, are one of the major factors influencing the geographical distribution of species diversity. Energy availability is often considered a crucial limiting factor, with temperature and productivity serving as empirical measures. However, these measures may not fully explain the observed species richness, particularly in marine ecosystems. Here, through a global comparative approach and standardised methodologies, such as Autonomous Reef Monitoring Structures (ARMS) and DNA metabarcoding, we show that the seasonality of primary production explains sessile animal richness comparatively or better than surface temperature or primary productivity alone. A Hierarchical Generalised Additive Model (HGAM) is validated, after a model selection procedure, and the prediction error is compared, following a cross-validation approach, with HGAMs including environmental variables commonly used to explain animal richness. Moreover, the linear effect of production magnitude on species richness becomes apparent only when considered jointly with seasonality, and, by identifying world coastal areas characterized by extreme values of both, we postulate that this effect may result in a positive relationship in environments with lower seasonality.

Ecogeographic Study of Ipomoea Species in Mauritius, Indian Ocean.

The wild relatives of crops play a critical role in enhancing agricultural resilience and sustainability by contributing valuable traits for crop improvement. Shifts in climatic conditions and human activities threaten plant genetic resources for food and agriculture (PGRFA), jeopardizing contributions to future food production and security. Studies and inventories of the extant agrobiodiversity, in terms of numbers and distribution patterns of species and their genetic diversity, are primordial for developing effective and comprehensive conservation strategies. We conducted an ecogeographic study on Ipomoea species and assessed their diversity, distribution, and ecological preferences across different topographic, altitudinal, geographical, and climatic gradients, at a total of 450 sites across Mauritius. Species distribution maps overlaid with climatic data highlighted specific ecological distribution. Principal Component Analysis (PCA) revealed species distribution was influenced by geographical factors. Regional richness analyses indicated varying densities, with some species exhibiting localized distributions and specific ecological preferences while the other species showed diverse distribution patterns. Field surveys identified 14 species and 2 subspecies out of 21 species and 2 subspecies of Ipomoea reported in Mauritius. A gap in ex situ germplasm collections was observed and several species were identified as threatened. Further investigations and a more long-term monitoring effort to better guide conservation decisions are proposed.

Distribution of Mangrove Species Diversity Along Environmental Variables Using Canonical Correspondence Analysis in Brgy. Penaplata, Samal City, Philippines

The main objective of this study is to assess the mangrove biodiversity in response to environmental changes, specifically its relationship between environmental variables and mangrove species biodiversity by evaluating the indicators in terms of abundance, richness, and evenness, alongside an analysis using Canonical Correspondence Analysis. Mangrove forest plays a significant role that caters to potential services like reductions of atmospheric carbon and has been the center for conservation due to its high importance to marine ecology. Based on the findings of the study, it was revealed that the area located in Brgy. Peñaplata, Samal City, Philippines, seven mangrove species were identified, classified into four families: <i>Avicennia alba, Avicennia marina</i>, and <i>Avicennia rumphiana</i> in the Avicenniaceae family; <i>Rhizophora apiculata, Rhizophora mucronata</i>, and <i>Rhizophora stylosa</i> in the Rhizophoraceae family; and <i>Sonneratia alba</i> in the Lythraceae family<i>. Rhizophora mucronata</i> emerged as the most abundant species, comprising 35.5% of total individuals. Moreover, the area determined to have low diversity due to the dominance of <i>Rhizophora mucronate</i> and <i>Avicennia alba</i>, leading to an unbalanced ecosystem, except in plot 3, which showed a more balanced and diverse mangrove ecosystem. Overall, significant correlations with the use of CCA were found, highlighting the positive influence of pH, temperature, TDS, and conductivity on mangrove species patterns and distribution. The findings of this study could support shape strategies for conserving and safeguarding mangrove ecosystems in Samal City, and maybe throughout the Philippines.

Insights into the molecular network characteristics of major HIV-1 subtypes in developed Eastern China: a study based on comprehensive molecular surveillance data.

This study aimed to conduct a comprehensive molecular epidemiology study of major HIV-1 subtypes in developed Eastern China (Zhejiang Province). Plasma samples and epidemiological information were collected from 4180 newly diagnosed HIV-1 positive patients in Zhejiang Province in 2021. Pol sequences were obtained to determine the subtypes via multiple analytical tools. HIV-1 molecular networks were constructed on the basis of genetic distances to analyze transmission patterns among major subtypes. Furthermore, the birth-death skyline (BDSKY) model was utilized to estimate the transmission risks associated with large clusters (LCs). In 4180 patients, 3699 (88.49%) pol sequences were successfully obtained and classified into four subtype groups. In the networks under an optimal genetic distance of 0.01 substitutions/site, the majority of links (74.52%, 1383/1856) involved individuals within the same city, highlighting the predominant role of local transmission in driving the HIV-1 epidemic. In the CRF07_BC, CRF01_AE, and others/URFs networks, men who have sex with men (MSM) were the primary sexual transmission population, with the younger MSM group (< 30 years old) exhibiting higher linkage frequencies. Within the CRF08_BC network, 93.98% of individuals were infected primarily through heterosexual contact and had a significantly greater risk of localized clustering than other subtypes did. Moreover, fifteen identified LCs were predominantly transmitted through commercial heterosexual contact (CHC), exhibiting localized clustering and high potential for sustained diffusion. Overall, our findings reveal a diverse and heterogeneous distribution of HIV-1 subtypes in Zhejiang Province, with noticeable variations in hotspots across different geographic areas and populations.

Bioecology of blackflies (Diptera: Simuliidae) of the water basin of the Huebra River (Western Spain)

The objectives of this study were to analyse the diversity and geographical distribution of the blackfly species from the Huebra River basin located in Salamanca province, Western Spain. This research significantly contributes to expanding our knowledge of the Simuliidae family. The study not only increases and ameliorates faunal and bioecological data, but also enhances the understanding of blackfly species across the Spanish national territory. The identification of 23 species has led to the addition of six new records to the simuliid fauna of the region: Simulium (Nevermannia) armoricanum Doby &amp; David, 1961; Simulium (Nevermannia) carthusiense Grenier &amp; Dorier, 1959; Simulium (Nevermannia) naturale Davies, 1966; Simulium (Nevermannia) vernum Macquart, 1826; Simulium (Simulium) bezzii (Corti, 1914) and Urosimulium faurei (Bernard, Grenier &amp; Bailly-Choumara, 1972), expanding the previously recorded 19 species to 25. This study also provides valuable insights into the biology and geographical distribution of these species. It sheds light on the ranges of altitude, water velocity, temperature and the depth of watercourses conducive to preimaginal development. Additionally, it offers new information on the abundance of larvae and pupae, revealing the diverse ecological gradients that influence their occurrence and distribution patterns. The results indicate that the diversity of blackfly species varies according to factors such as altitude, water velocity, turbidity, and water temperature.

Decolonizing AI: Implementing Humanitarian Artificial Intelligence

In this article, we critically examine the implementation of what Carlos Montemayor calls Humanitarian Artificial Intelligence from a decolonizing perspective. We highlight the dichotomy of optimism and fear surrounding AI, elucidating its potential to address fundamental human problems and the risks of monopolistic control. We critique Montemayor’s proposal to align AI with a human rights framework, arguing that it insufficiently addresses global inequalities. Our tripartite analysis focuses on the distribution of AI resources, language inclusion, and content diversity to ensure AI benefits all humanity. We emphasize the need for equitable access to AI, linguistic diversity in AI training data, and the preservation of marginalized epistemologies. We advocate for strategies to mitigate environmental impacts and avoid cultural imperialism disguised as altruism, calling for a balanced approach between private sector innovation and state regulation to foster a truly humanitarian AI.

Molecular diversity and seasonal dynamics of Ostreococcus (Mamiellophyceae, Chlorophyta) in typical mariculture bays based on metabarcoding analysis

Ostreococcus (Mamiellophyceae, Chlorophyta) is a cosmopolitan genus of marine pico-phytoplankton and the smallest free-living photosynthetic eukaryotes with cell size of 1–2 μm. To understand the diversity and spatio-temporal distribution of Ostreococcus in the Rongcheng coastal regions in northern China, metabarcoding analysis based on the 18S rDNA V4 molecular marker was applied to study the molecular diversity and seasonal dynamics of Ostreococcus in three typical mariculture bays (Rongcheng Bay, Lidao Bay and Sanggou Bay). A total of 103 amplicon sequence variants (ASVs) annotated as Ostreococcus were detected in these three typical mariculture bays throughout the year. The top five ASVs in terms of abundance were ASV4, ASV9, ASV14, ASV28 and ASV109, totally occupying 99.1% of Ostreococcus reads. Phylogenetic analysis showed that these five dominant ASVs represented two Ostreococcus ecotypes (OI and OII) and were grouped into four Ostreococcus clades including Ostreococcus lucimarinus (ASV9) and Ostreococcus tauri (ASV28 and ASV109) in OI, and Ostreococcus sp. RC1 (ASV4) and Ostreococcus sp. RC2 (ASV14) in OII, which provided direct evidence to support the co-existence of two ecotypes in the Rongcheng coastal regions. Five dominant ASVs in OI and OII exhibited two distinct seasonal distribution patterns. Three dominant ASVs (ASV9, ASV28 and ASV109) in OI could be detected in all four seasons of the year, exhibiting native distribution properties, while two ASVs (ASV4 and ASV14) in OII decreased sharply in winter and could not be detected in spring, exhibiting characteristics of alien inputs. The composition, succession and association of Ostreococcus community were mainly driven by water temperature in these mariculture bays. This study helps us systematically understand the molecular diversity and distribution patterns of Ostreococcus in typical mariculture bays in northern China, laying the foundation for understanding and revealing the ecological functions of pico-phytoplankton.

Analysis of the Interrelation and Seasonal Variation Characteristics of the Spatial Niche of Dominant Fishery Species-A Case Study of the East China Sea.

The spatial niche has garnered significant attention in ecological research, particularly regarding species distribution patterns. The East China Sea, known for its favorable natural conditions and abundant fishery resources, exhibits diverse spatial distribution patterns among species, shaped by their seasonal physiological needs. This study utilized a habitat suitability index model to explore the spatial distribution patterns of key fishery resources in the East China Sea across four seasons and their interactions. Two methodologies were employed to identify key environmental factors and assess the ecological niche overlap among different species and seasons. Results indicated that the initial method identified water temperature as the critical factor for hairtail, while the subsequent method emphasized water temperature and salinity for hairtail, salinity for small yellow croaker, and water depth for Bombay duck. The main spatial habitat overlap was observed between paired species, likely driven by predator-prey interactions. During summer and autumn, increased overlap among multiple species was primarily influenced by synchronized life cycles. An overlap index formula quantified the seasonal species overlap, showing an increase from spring to winter, reflecting changes in convergent habitat preferences. The peak overlap occurred in winter, driven by overwintering, reduced food competition, and enhanced coexistence potential, while the lowest overlap was noted in spring as overwintering ended and predation and competition intensified.

Fine-scale phylogeography of Tripneustes gratilla revealed a core-periphery pattern in the South China sea

The Core-Periphery Hypothesis (CPH) is a theoretical framework in phylogeography used to examine the spatial distribution of genetic diversity. The tropical Indian-Western Pacific (IWP), serving as a prominent marine biodiversity hotspot, constantly exports species and evolutionary novelties to peripheral habitats. Many species display genetic patterns consistent with CPH predictions from the IWP to periphery regions. However, the presence of CPH’s genetic signals in intermediate distribution zones remains underexplored. Here, we collected four sea urchin populations of Tripneustes gratilla in the South China Sea and analysed their population structure and evolutionary patterns using 13 morphological parameters, one mitochondrial 16S rRNA gene and nine polymorphic microsatellites. The results revealed substantial genetic homogeneity among the populations, implying a single origin from a glacial refugium. Nonetheless, morphological and microsatellite data distinctly differentiate the northernmost Fengjiawan population from the others, which could be attributed to increased environmental selection pressures such as temperature. Analysis of genetic diversity variation along latitudinal gradients and the relationship between geographic and genetic distances align with CPH expectations for both 16S and microsatellites, albeit to varying degrees of significance. This study enhances our understanding of tropical marine invertebrate evolution and supports the applicability of the CPH model at a fine-scale level.

The RAS/BRAF genes status in patients with colorectal cancer (review)

Colorectal cancer (CRC) is the third in prevalence among oncological diseases worldwide and second in the structure of oncological mortality. Genetic assessment of CRC is a necessary stage during selecting further treatment for patients. Many studies demonstrate a diverse distribution of mutations in the KRAS, NRAS, and BRAF genes in CRC. A critical literature review was conducted in order to systematize data on the mutational profile and genetic heterogeneity of these driver mutations in Russian patients with CRC. Articles were searched for in open databases. Totally 17 Russian studies and 3 English meta-analyses were analyzed for comparison with Russian data. Mutations in the KRAS, NRAS, and BRAF genes, according to Russian and international studies, are found in 40 %, 4 %, and 7 % in CRC patients, respectively. The frequency and specific localization of mutations may depend on the geographical location and nationality of the cohort. High intertumoral and intratumoral heterogeneity in CRC, especially in KRAS gene mutations, significantly influences the choice of further therapy and underscores the need for more detailed study of the mutational profile of the primary tumor, affected lymph nodes, and distant metastases. In Russia, several molecular genetic methods are used to determine somatic mutations in CRC with different sensitivity and specificity, the most common is real-time PCR. More accurate diagnostic methods include digital droplet PCR, Sanger sequencing, and next-generation sequencing, but each method has its limitations that must be considered when planning diagnostics and research. The promising directions in personalized oncology is the study of gene copy number variations, which may contribute to the development of new methods for treating CRC in the future. Despite the large number of studies, some aspects of the mutational profile of CRC in Russian studies remain poorly understood, which is why further research is needed on patients with colorectal cancer in Russia.

Microbial profiling of oysters from a processing plant and retail products: Analysis based on culture-dependent methods and 16S rRNA gene sequencing

Oysters (Crassostrea gigas) are one of the most consumed shellfish globally. However, there is a lack of comprehensive microbiome studies that include the processing and distribution stages of oysters. The present study used both culture-based methods and 16S rRNA sequencing to produce comprehensive microbial profiles of oysters in two parts: (1) an oyster processing plant that processes raw and frozen oysters (n = 57) and (2) retail oyster products across two seasons (winter and spring) (n = 112). In the processing plant, shucking increased the aerobic plate count (APC) from 1.86 log CFU/g in freshly harvested oysters to 3.95 log CFU/g in shucked oysters. Controlling the washing process is important, as the APCs decreased after washing and remained level until the final products, raw and frozen oysters (2.54 and 2.34 log CFU/g, respectively). After desalting in the frozen oyster plant, the bacterial community shifted to be dominated by the family Spirochaetaceae, Mycoplasma, and Shigella taxa, indicating a need to control problematic bacteria in the desalting process. SourceTracker analysis revealed that raw materials contributed more to the microbiota of final products than environmental samples. In retail oyster products, APCs were marginally higher in spring (3.58 log CFU/g) than in winter (3.05 log CFU/g) samples. While bacterial count differences were not dramatic, the proportions of taxa in the microbial community differed by season. In winter retail products, Photobacterium (27.91 %) and Aliivibrio (20.42 %) dominated, while spring samples showed a diverse distribution of the family Vibrionaceae (19.90 %), Photobacterium (14.20 %), Psychromonas (11.84 %), and Aliivibrio (7.20 %). These findings contributed to our understanding of oyster microorganisms and identified food safety control points and cross-contamination sources. This in-depth understanding is expected to inform the development of fishery and seafood safety management measures.

Towards zero extinction—A case study focusing on the plant genus Begonia in Thailand

AbstractPlant species with small habitat ranges and specific edaphic requirements are highly vulnerable to extinction and thus require enhanced attention in biodiversity conservation. This study was designed to explore the challenges of protecting such plant species by evaluating the in situ and ex situ conservation capacities available for Thailand's species of the mega‐diverse plant genus Begonia L. A comprehensive assessment of occurrence records across the country was conducted to evaluate the spatial distribution of Begonia diversity in Thailand, identify biodiversity hotspots, assess the extinction threats faced by the 60 Begonia species known in the country, and identify existing conservation capacities and potential gaps. The results show that 78% of Begonia species in Thailand are vulnerable to extinction, with the Northern floristic region identified as both a Begonia species hotspot and a region with major conservation gaps. While in situ conservation efforts have been successful in covering over 88% of the species, they have failed to provide the protection required to achieve zero extinction. Ex situ conservation capacities are poorly developed, with only 13% of species present in botanical gardens, and no seed banking or other related activities have been initiated. This evaluation presents a sharply contrasting message: on one hand, Thailand has assembled substantial capacities to protect these plants through established national parks and other protected areas, but on the other hand, essential capacities are still lacking to render the zero extinction target achievable. We advocate for the implementation of a multi‐component conservation strategy to enable Thailand to move towards zero species extinction, even for plant species with narrow habitat ranges and high edaphic specialisation.

A High-Resolution and Robust Microwave Correlation Imaging Method Based on URRF Using MC-AAMPE Algorithm

This manuscript presents a novel framework for high-resolution and robust microwave correlation imaging. In order to generate a more diverse random radiation field distribution, the unified random radiation field (URRF) model is proposed. The URRF model can accurately characterize the joint random modulation in the signals’ phase, amplitude, and frequency. Furthermore, we build a parametric imaging model based on URRF which clearly describes the relationship between the image to be reconstructed and the signals by the URRF model. By using this imaging model, the reconstruction of an image is converted into solving a multi-parameter optimization problem with multiple constraints. To solve this optimization problem with high efficiency and accuracy, the model-constrained adaptive alternating multiple parameter estimation (MC-AAMPE) algorithm is proposed. This algorithm decomposes the high-dimensional multi-parameter optimization problem into several sub-optimization problems. The renewing solutions to these sub-optimization problems make the multi-parameter optimization converge to the image of the target and the parameters of clutter and noise, which are all unknown before the solution. In comparison with the existing methods, the proposed scheme generates images with higher resolution and is more robust under noise conditions. Extensive simulation experiments confirmed the effectiveness and robustness of the proposed method.

Global burden of benign prostatic hyperplasia, urinary tract infections, urolithiasis, bladder cancer, kidney cancer, and prostate cancer from 1990 to 2021

BackgroundThe burden of common urologic diseases, including benign prostatic hyperplasia (BPH), urinary tract infections (UTI), urolithiasis, bladder cancer, kidney cancer, and prostate cancer, varies both geographically and within specific regions. It is essential to conduct a comprehensive and precise assessment of the global burden of urologic diseases.MethodsWe obtained data on incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) for the aforementioned urologic diseases by age, sex, location, and year from the Global Burden of Disease (GBD) 2021. We analyzed the burden associated with urologic diseases based on socio-demographic index (SDI) and attributable risk factors. The trends in burden over time were assessed using estimated annual percentage changes (EAPC) along with a 95% confidence interval (CI).ResultsIn 2021, BPH and UTI were the leading causes of age-standardized incidence rate (ASIR) and age-standardized prevalence rate (ASPR), with rates of 5531.88 and 2782.59 per 100,000 persons, respectively. Prostate cancer was the leading cause of both age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR), with rates of 12.63 and 217.83 per 100,000 persons, respectively. From 1990 to 2021, there was an upward trend in ASIR, ASPR, ASMR, and ASDR for UTI, while urolithiasis showed a downward trend. The middle and low-middle SDI quintile levels exhibited higher incidence, prevalence, mortality, and DALYs related to UTI, urolithiasis, and BPH, while the high and high-middle SDI quintile levels showed higher rates for the three cancers. The burden of these six urologic diseases displayed diverse age and sex distribution patterns. In 2021, a high body mass index (BMI) contributed to 20.07% of kidney cancer deaths worldwide, while smoking accounted for 26.48% of bladder cancer deaths and 3.00% of prostate cancer deaths.ConclusionsThe global burden of 6 urologic diseases presents a significant public health challenge. Urgent international collaboration is essential to advance the improvement of urologic disease management, encompassing the development of effective diagnostic screening tools and the implementation of high-quality prevention and treatment strategies.

Region‐specific diversification dynamics and biogeographic history of one of the most diverse families of insects

AbstractA long‐standing question in evolutionary biology is how historical biogeographic processes have shaped the current diversity of organisms, especially for highly diverse groups. We study the diversification dynamics and biogeographic processes of one of the most diverse families of Lepidoptera, Geometridae, with over 24,000 described species and a worldwide distribution. Despite the cosmopolitan distribution of the family, most species of Geometridae have limited distribution ranges. We present the largest historical biogeography and diversification study on the current diversity patterns and distribution ranges of Geometridae. We use a multi‐locus dataset of 1200 taxa to estimate the historical biogeography of Geometridae, implementing a Bayesian approach of the Dispersal‐Extinction‐Cladogenesis (DEC) model that incorporates palaeographic‐based dispersal graphs with uncertainty in geological ages in RevBayes. We also implement a Bayesian time‐variable, episodic birth–death model and a model that allows branch‐specific speciation rates to estimate the diversification dynamics in the family. Our results suggest that the most recent common ancestor of Geometridae was distributed in the New World, with the Neotropics being the most likely ancestral area. An increase in diversification rates occurred circa 30–40 million years ago (Mya), coinciding with a time of a major global climate cooling in the Eocene. Clade‐specific shifts in speciation rates also occurred around 10–15 Mya, coincident with another period of major climate change in the Oligocene. Our results point to different biogeographical and evolutionary histories per area to show the differences of the diversification rates in different biogeographical regions through time, showing the relative importance of each region in the diversification history of Geometridae.

GEPAF: A non-monotonic generalized activation function in neural network for improving prediction with diverse data distributions characteristics

The world today has made prescriptive analytics that uses data-driven insights to guide future actions. The distribution of data, however, differs depending on the scenario, making it difficult to interpret and comprehend the data efficiently. Different neural network models are used to solve this, taking inspiration from the complex network architecture in the human brain. The activation function is crucial in introducing non-linearity to process data gradients effectively. Although popular activation functions such as ReLU, Sigmoid, Swish, and Tanh have advantages and disadvantages, they may struggle to adapt to diverse data characteristics. A generalized activation function named the Generalized Exponential Parametric Activation Function (GEPAF) is proposed to address this issue. This function consists of three parameters expressed: α, which stands for a differencing factor similar to the mean; σ, which stands for a variance to control distribution spread; and p, which is a power factor that improves flexibility; all these parameters are present in the exponent. When p=2, the activation function resembles a Gaussian function. Initially, this paper describes the mathematical derivation and validation of the properties of this function mathematically and graphically. After this, the GEPAF function is practically implemented in real-world supply chain datasets. One dataset features a small sample size but exhibits high variance, while the other shows significant variance with a moderate amount of data. An LSTM network processes the dataset for sales and profit prediction. The suggested function performs better than popular activation functions when a comparative analysis of the activation function is performed, showing at least 30% improvement in regression evaluation metrics and better loss decay characteristics.

Comprehensive analysis of radiological and surgical predictors in cervical sympathetic schwannomas: a novel staging approach and its implications.

Vagal schwannomas are well-documented, but cervical sympathetic chain schwannomas (CSCS) are rare, with most knowledge from case reports. This study aims to identify radiological predictors of misdiagnosis and factors guiding surgical approaches based on tumor size and extent. An ambispective analysis was conducted on 21 cases of CSCS, examining preoperative data, intraoperative findings and the questionnaire to identify the potential predictors. Tumors were classified into three types based on their relationship with the carotid sheath, and this classification was correlated with vessel ligation and postoperative neural outcomes. An excellent agreement was found between radiologist on new classification system(Kappa:0.89). Tumor classification revealed a diverse distribution, with 6 cases identified as Type 1, 6 as Type 2, 5 as Type 3, and 4 as Type 3S. The necessity of external carotid artery (ECA) ligation correlated with the tumor type. Type 3 tumors required ECA ligation in 50% of cases, while Type 1 and Type 2 tumors predominantly involved vascular preservation. Postoperative complications included vagal palsy in 28.5% of cases and first bite syndrome in 71.4%. Accurate preoperative planning and a novel staging system can enhance surgical outcomes and reduce postoperative complications as validated by our study.

Structure and distribution of sensor histidine kinases in the fungal kingdom.

Two-component systems (TCSs) are diverse cell signaling pathways that play a significant role in coping with a wide range of environmental cues in both prokaryotic and eukaryotic organisms. These transduction circuitries are primarily governed by histidine kinases (HKs), which act as sensing proteins of a broad variety of stressors. To date, nineteen HK groups have been previously described in the fungal kingdom. However, the structure and distribution of these prominent sensing proteins were hitherto investigated in a limited number of fungal species. In this study, we took advantage of recent genomic resources in fungi to refine the fungal HK classification by deciphering the structural diversity and phylogenetic distribution of HKs across a large number of fungal clades. To this end, we browsed the genome of 91 species representative of different fungal clades, which yielded 726 predicted HK sequences. A domain organization analysis, coupled with a robust phylogenomic approach, led to an improved categorization of fungal HKs. While most of the compiled sequences were categorized into previously described fungal HK groups, some new groups were also defined. Overall, this study provides an improved overview of the structure, distribution, and evolution of HKs in the fungal kingdom.

Genome-Based Analysis of Genetic Diversity, Antimicrobial Susceptibility, and Virulence Gene Distribution in Salmonella Pullorum Isolates from Poultry in China.

Pullorum disease, caused by Salmonella enterica serovar Pullorum (S. Pullorum) infection, is a major pathogenic threat to the poultry industry. In this study, 40 S. Pullorum isolates from seven provinces of China were comprehensively analyzed in terms of antigenic type and antimicrobial susceptibility, and their drug-resistance genes and virulence genes were identified with whole-genome sequencing (WGS). We show that all these isolates were standard antigenic types, with ST92 the predominant genotype (92.5%). Disk diffusion assays revealed high resistance rates to streptomycin (92.5%), ciprofloxacin (82.5%), and ampicillin (80%), and the resistance rates to streptomycin, gentamicin, ampicillin, and cefotaxime were higher in isolates from sick chickens than in those from healthy chickens. In addition, gyrA mutations and eight acquired resistance genes were identified, with aac(6')-Iaa the most prevalent, followed by blaTEM1β, sul2, and the GyrA S83F mutation. The resistance phenotypes to streptomycin, ampicillin, and ciprofloxacin correlated strongly with the presence of the aac(6')-Iaa resistance gene, blaTEM1β resistance gene, and gyrA mutations, respectively. Analysis of the virulence genes showed that the isolates expressed numerous factors associated with secretion systems, including SPI-1 and SPI-2. Overall, this study extends our understanding of the epidemiology and antibiotic resistance of S. Pullorum in China.

The Relationship between Family Functioning, Emotional Intelligence, Loneliness, Social Support, and Depressive Symptoms among Undergraduate Students.

The transition from adolescence to college is a significant developmental stage marked by challenges such as high academic pressure, changes in living environments, and social support systems. These challenges can lead to increased rates of depression among college students. This study investigates the relationships between family functioning, emotional intelligence, loneliness, social support, and depressive symptoms in Chinese college students. A cross-sectional design was employed, with data collected via questionnaires from undergraduate students at Xi'an Jiaotong University. Variables such as family functioning, emotional intelligence, loneliness, social support, and depressive symptoms were assessed. Statistical analyses, including correlation and hierarchical regression, were conducted to explore these relationships. The study found a diverse distribution of depressive symptoms among students, with significant gender differences indicating higher depression rates in females. No significant differences were observed across academic disciplines, grades, or between only children and non-only children. Family functioning, emotional intelligence, and social support were negatively correlated with depressive symptoms, while loneliness was positively correlated. Hierarchical regression analysis confirmed that social support significantly moderated the relationship between family functioning and depressive symptoms. Mediation analysis showed that emotional intelligence and loneliness mediated this relationship. The findings highlight the complex interplay between family dynamics, emotional capabilities, social connectedness, and mental health. Enhancing family functioning, emotional intelligence, and social support can effectively reduce depressive symptoms among college students. These results underscore the need for holistic interventions that address multiple aspects of students' social and emotional lives.